Designing a motion estimation approach for a very large scale integration implementation that yields high picture quality (i.e., DVD quality) while consuming very low external memory bandwidth poses several challenges. Using a large search area for the motion estimation yields high picture quality but uses very high external memory bandwidth and large internal buffers. Using a small search area for the motion estimation results in reduced external memory bandwidth, but produces additional controls, buffering and yields low picture quality, especially in the presence of fast motion. To counter the fast motion, each target macroblock can be searched in a small, localized area. However, little or no overlap exists between localized search areas for each target macroblock, or group of macroblocks, in a worst case scenario. Thus, very high external memory bandwidth is still consumed reading reference data for each small search areas.
A first approach for motion estimation is to encode with a regular search method using small motion estimation search areas. However, the first approach suffers from a picture quality loss. A second approach is to encode with the regular search method using large motion estimation search areas. Consequences for using the large search areas include high external memory bandwidth, a large internal memory buffer and large computational complexity. A third approach is to encode with “fast” search methods that use fewer data points (i.e., fewer calculations per search location and/or fewer search locations) and small motion estimation search areas. The fewer data points result in a moderate external memory bandwidth usage but produce a picture quality loss while adding complexity in the forms of additional control and buffering. A fourth approach is to encode with “fast” search methods and large motion estimation search area. The large search areas consume a high external memory bandwidth, large internal memory buffers and produce additional control and buffering.